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The most reliable way to monitor Sui is to combine three views: an explorer for a single transaction, GraphQL for repeatable queries and dashboards, and gRPC or an indexer for continuous, high-volume data. For each transaction, record its execution status, checkpoint or timestamp, submitted gas price, gas budget, and final net gas fee. Compare the submitted gas price with that epoch’s reference gas price, but do not treat a tip alone as a network-wide congestion score.
Sui separates computation and storage charges, then subtracts a storage rebate to calculate the net fee. The gas budget is only a spending limit; it is not the amount necessarily paid. The sections below show how to inspect those values, automate collection, select an access method, and interpret congestion signals without confusing a transaction-level observation with the condition of the entire network.
What you should monitor on Sui
A useful monitoring setup answers four different questions:
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- Did this transaction finish? Check its execution status and, when available, the checkpoint that contains it.
- What did it cost? Capture gas price, gas budget, the computation and storage components, storage rebate, and the resulting net gas fee.
- What was the network’s pricing context? Compare the transaction gas price with the reference gas price for its epoch.
- Can the data feed keep up? Measure endpoint errors, pagination progress, subscription health, and retention when building a service.
These are related but not interchangeable. A large gas budget does not prove that a transaction paid a large fee. A high gas price can reflect a user-selected tip rather than congestion across the whole network. An RPC timeout may indicate an overloaded endpoint rather than a congested Sui protocol.
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Transaction-level facts versus network-level signals
An explorer or RPC response tells you what happened to one transaction. Network monitoring requires a series of observations over time and, ideally, more than one signal. Sui documentation describes tips as a market-based mechanism for extreme congestion, so a tip above the epoch reference price is useful context. It is not a published universal congestion threshold or a complete congestion index.
Quick check: inspect one transaction in an explorer
Use this workflow when someone gives you a transaction digest or when an application reports an uncertain result.
- Open a Sui explorer and search the transaction digest. Paste the complete digest rather than an account address or object identifier.
- Confirm execution status. Record whether the transaction succeeded or failed and preserve the displayed error details for a failed execution.
- Record its checkpoint and timestamp. The checkpoint places the transaction in Sui’s finalized sequence; the timestamp helps you compare observations from different periods.
- Read the gas price and gas budget. These are submitted transaction parameters. The budget caps the gas that may be spent; it is not a receipt for the final charge.
- Record the explorer’s net gas fee. Sui’s gas documentation says the explorer displays the net fee for each transaction. Use this value when reporting what the transaction actually cost.
- Note the epoch reference gas price. If the explorer exposes it, save it alongside the transaction gas price so that any tip can be calculated and reviewed in context.
Keep the digest, status, checkpoint, timestamp, gas price, budget, reference price, and net fee together in a log. That prevents a later investigation from mistaking a budget or quoted estimate for the settled charge.
How Sui gas fees are calculated
The net-fee formula
Sui defines the net gas fee as:
net gas fee = computation gas fee + storage gas fee − storage rebate
Computation gas pays for execution work. Storage gas covers state written by the transaction. The storage rebate returns an amount associated with storage that is later released under Sui’s storage economics. The explorer’s net value is therefore the right number for an after-the-fact cost report, while the component values explain why two transactions with similar execution paths can have different totals.
Three values that must not be confused
| Value | What it means | How to use it |
|---|---|---|
| Gas budget | The maximum spending permitted for the transaction | Use it to detect an overly tight or unusually generous limit; do not report it as the fee paid. |
| Submitted gas price | The price offered for computation, including any tip above the epoch reference price | Compare it with the reference price for the same epoch. |
| Net gas fee | Computation and storage charges after subtracting the storage rebate | Use it as the settled transaction cost shown by the explorer. |
Gas-budget limits in current documentation
Current Sui gas documentation lists a minimum gas budget of 2,000 MIST (0.000002 SUI) and a maximum of 50 billion MIST (50 SUI). The same documentation states that storage rebates currently equal 99% of originally paid storage fees. These are implementation details that can change; verify the values against the documentation used by your network and software version before hard-coding validation rules.
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Reference gas price, tips, and congestion
Use the epoch reference price as an anchor
Sui validators update the reference gas price at epoch boundaries. A transaction’s gas price can equal that reference price or include a higher tip. Compute the difference for the same epoch:
tip = transaction gas price − epoch reference gas price
If the result is zero, the transaction did not offer a price premium over the reference. If it is positive, the sender offered a tip. Store the epoch identifier with both prices; comparing a transaction with the reference price from a different epoch can produce a misleading result.
Why a tip is only one signal
Sui documentation explains that, during extreme congestion when validators cannot scale fast enough, the presence of tips can provide market-based congestion pricing by discouraging additional demand. That statement does not define a public threshold at which the network is “congested,” and it does not say that every tip means the whole network is congested. A sender may choose a premium for its own urgency, or an application may configure one routinely.
For a more defensible dashboard, display the tip alongside transaction outcomes, checkpoint progression, observed finalization times, and your endpoint’s error or throttling rate. Label these as operational indicators rather than protocol-defined congestion grades. Avoid publishing a single red-line number unless you have established and documented it from your own workload.
Query transaction and epoch data with GraphQL
GraphQL RPC is the practical starting point for dashboards, investigations, and application backends that need to select only the fields relevant to a question. Sui’s documented examples cover transaction gas sponsor, gas price, gas budget, status, timestamp, checkpoint, the epoch reference gas price, and historical epoch total gas fees.
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Fields to collect for a transaction
- Transaction digest
- Gas sponsor or owner, when your audit requires it
- Gas price and gas budget
- Execution status and failure information
- Checkpoint and timestamp
- Gas summary fields for computation cost, storage cost, and storage rebate when exposed by the endpoint schema
- Epoch identifier, so the correct reference price can be joined to the transaction
Fields to collect for an epoch
- Epoch identifier
- Reference gas price
- Total gas fees for historical comparisons
Illustrative query shape
GraphQL schemas evolve, so inspect the schema exposed by your endpoint and adjust field names or nesting before deploying. The following shape shows how to request the documented categories without assuming that one response contains every historical record:
query TransactionAndEpoch($digest: String!) {
transactionBlock(digest: $digest) {
digest
gasInput { gasPrice gasBudget }
effects {
status { status }
gasEffects {
gasSummary {
computationCost
storageCost
storageRebate
}
}
}
checkpoint { sequenceNumber }
timestamp
epoch { epochId referenceGasPrice totalGasFees }
}
}Use schema introspection or the endpoint’s current examples to confirm the exact names and scalar types. If your endpoint separates epoch queries from transaction queries, request the transaction’s epoch identifier first and then retrieve that epoch’s reference price.
Paginate every large query
Do not assume that a single GraphQL response contains all transactions, checkpoints, or events. Request a bounded page, follow the returned cursor or page-information fields, and persist the cursor only after successfully storing the page. On restart, resume from the last confirmed cursor. This avoids gaps when a process stops between requests and prevents an unbounded response from exhausting memory.
Choose the right data-access method
| Need | Best fit | What to plan for |
|---|---|---|
| Flexible one-off queries or a dashboard across transactions, checkpoints, events, and balances | GraphQL RPC | Select only needed fields and paginate large result sets. |
| High-throughput live ingestion | gRPC | Subscribe to finalized checkpoints and request only the transaction and event data your pipeline uses. |
| Custom joins, derived metrics, or long-term retention | Application-specific indexer | Define a data model, replay strategy, retention period, and handling for reprocessing. |
| History no longer retained by a pruned full node | Archival store or service | Use an archival source for complete historical lookup rather than assuming a recent-history RPC can answer it. |
| Control over availability, retention, and read performance | Self-operated full node plus monitoring | Budget for operations, storage, upgrades, backups, and health instrumentation. |
GraphQL for dashboards and investigations
GraphQL is well suited to a dashboard that lets an analyst choose an address, digest, epoch, or time range and then requests the matching fields. It also works for moderate-volume application backends where query flexibility matters more than a continuous event stream.
gRPC for a live pipeline
For high-throughput monitoring, Sui recommends gRPC and documents subscriptions to finalized checkpoints with selected transaction and event data. A checkpoint subscription lets an ingestion service process a stream instead of repeatedly polling for new records. Persist the last processed checkpoint and make your consumer idempotent so reconnects do not create duplicate metrics.
When to build an indexer
Build an application-specific index when you need joins, derived measures, custom retention, or a query shape that direct RPC calls cannot provide efficiently. Keep raw identifiers such as digest, checkpoint, epoch, and timestamp so that a derived record can be traced back to its source. Decide how to handle schema changes and replay before relying on the index for accounting.
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When archival access is necessary
Full nodes may prune older data. If an investigation requires history beyond the node’s retention window, use an archival store or service. Treat archival availability and completeness as separate requirements: confirm that the source covers the epochs and object history your audit needs.
Public endpoints and production reliability
Public Sui GraphQL endpoints are rate-limited and intended for development or public-good access. They are useful for learning, prototypes, and occasional checks, but a production monitor should not silently depend on an endpoint with unknown throughput or uptime.
Provider endpoint or self-operated infrastructure
A managed provider endpoint can reduce the operational burden when your team needs predictable access, while a self-operated stack gives you more control over capacity, retention, and upgrades. Choose between them using your required request rate, latency tolerance, historical depth, incident response capability, and budget. The official guidance does not establish a universal request quota, so do not design around an invented number.
Reliability controls for either option
- Set request timeouts and bounded retries with backoff.
- Record HTTP or RPC status, throttling responses, and schema errors separately from on-chain transaction failures.
- Track the age of the newest checkpoint you have ingested.
- Persist cursors or checkpoint positions so a restart can resume safely.
- Alert when ingestion stalls, but distinguish an endpoint outage from a protocol-level execution problem.
- Keep a second access path for incident investigation when the primary endpoint is unavailable.
Monitor a full node’s health separately
A full node is a state replica that serves RPC requests. If you operate one, use Sui’s monitoring guidance for node health and performance metrics in addition to collecting transaction and gas data. Check synchronization progress, resource saturation, request failures, and storage health according to the metrics exposed by your node version.
Node health answers whether your replica and service are functioning. It does not establish a universal public congestion threshold. A healthy node can observe a busy network, and an unhealthy node can make a normal network appear slow to your application.
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Build a practical congestion dashboard
Core panels
- Transaction outcomes: counts of successful and failed transactions, grouped by epoch or checkpoint.
- Gas pricing: transaction gas price, epoch reference price, and calculated tip.
- Net cost: computation, storage, rebate, and final net fee distributions.
- Finalization context: checkpoint and timestamp for each observation, plus the age of the newest ingested checkpoint.
- Data-pipeline health: request latency, error classes, throttling events, subscription reconnects, and ingestion lag.
How to label the dashboard
Use neutral labels such as “tip above reference,” “failed execution,” “ingestion lag,” and “endpoint throttling.” Do not label a transaction “network congestion” solely because its gas price is above reference. If you create an internal congestion score, document the inputs, time window, workload, and alert thresholds so users understand that it is an operational heuristic rather than an official Sui metric.
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Troubleshoot common monitoring mistakes
The explorer shows a fee larger or smaller than the budget
Recheck which value you recorded. The budget is a cap, while the net fee is calculated after execution from computation, storage, and rebate components. A transaction can consume less than its budget, and the rebate can reduce the net amount.
A transaction has a tip but the network looks normal
Compare the transaction price with the reference price for its own epoch, then inspect a broader sample. A sender’s urgency or application policy can explain an isolated premium. Do not infer a network-wide state from one digest.
Historical queries return incomplete results
Check whether the node has pruned the required period. If it has, switch the historical lookup to an archival source. Also verify that your GraphQL pagination loop followed every cursor and that your indexer did not discard older checkpoints during a migration.
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Requests fail intermittently
Separate rate limiting, transport failures, and GraphQL validation errors in logs. Reduce page size, add bounded backoff, and avoid sending concurrent bursts to a public endpoint. For sustained production traffic, evaluate a provider endpoint or operate infrastructure sized for the required throughput.
Your live stream contains duplicates after reconnecting
Persist the last finalized checkpoint processed and make writes idempotent using stable transaction or event identifiers. On reconnect, replay a small overlap and de-duplicate rather than assuming that the stream resumes exactly at the failure boundary.
A repeatable monitoring routine
- For an incident: inspect the digest in an explorer and save status, checkpoint, timestamp, gas price, budget, reference price, and net fee.
- For a daily report: query transaction and epoch fields through GraphQL, paginate all result sets, and store the raw identifiers with derived tip and net-fee fields.
- For continuous ingestion: subscribe through gRPC to finalized checkpoints, persist the checkpoint cursor, and make processing idempotent.
- For custom analytics: feed the stream into an index with an explicit retention and replay plan.
- For deep history: route requests beyond full-node pruning to archival access.
- For infrastructure operations: monitor node health and endpoint reliability separately from on-chain gas and execution metrics.
This separation keeps the accounting accurate: the explorer or execution data establishes what a transaction paid, the epoch reference price supplies pricing context, and a time series of transactions plus pipeline health provides the evidence needed to discuss congestion carefully.
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